With the prosperity of deep learning, the encoder-decoder framework becomes a prevailing approach to sequence generation. In particular, recurrent neural networks (RNNs) typically serve as the encoder and decoder; such architecture is also known as a sequence-to-sequence (Seq2Seq) model [1]}. When applied to code generation, it takes the program description as the input sequence and generates the desired code as the output sequence [2]}.
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